88 datasets found
  1. Share of people who have started their own business by country 2021

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Share of people who have started their own business by country 2021 [Dataset]. https://www.statista.com/statistics/948475/share-people-started-their-own-business-country/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 20, 2020 - Dec 4, 2020
    Area covered
    Worldwide
    Description

    According to data published by IPSOS in 2021, ** percent of respondents from Peru have started at least one business, compared to ***** percent of respondents from Japan.

  2. Established business ownership rate in North America, by country 2023

    • statista.com
    Updated Jul 4, 2025
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    Statista (2025). Established business ownership rate in North America, by country 2023 [Dataset]. https://www.statista.com/statistics/315556/established-business-ownership-rate-in-north-america/
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    Dataset updated
    Jul 4, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    North America
    Description

    In 2023, ***** percent of the adult population in the United States and ***** percent in Canada were owning and running an established business. Established business ownership rate refers to the percentage of 18-64 population who are currently owner-manager of an established business, i.e., owning and managing a running business that has paid salaries, wages, or any other payments to the owners for more than 42 months.

  3. 2018 Economic Surveys: AB1800CSCBO | Annual Business Survey: Owner...

    • data.census.gov
    + more versions
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    ECN, 2018 Economic Surveys: AB1800CSCBO | Annual Business Survey: Owner Characteristics of Respondent Employer Firms by Sector, Sex, Ethnicity, Race, and Veteran Status for the U.S., States and Metro Areas: 2018 (ECNSVY Annual Business Survey Characteristics of Business Owners) [Dataset]. https://data.census.gov/cedsci/table?n=00&tid=ABSCBO2018.AB1800CSCBO&nkd=QDESC~O11
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2018
    Area covered
    United States
    Description

    Release Date: 2021-01-28.The Census Bureau has reviewed this data product for unauthorized disclosure of confidential information and has approved the disclosure avoidance practices applied (Approval ID: CBDRB-FY20-424)...Release Schedule:.Data in this file come from estimates of business ownership by sex, ethnicity, race, and veteran status from the 2019 Annual Business Survey (ABS) collection. Data are also obtained from administrative records, the 2017 Economic Census, and other economic surveys...Note: The collection year is the year in which the data are collected. A reference year is the year that is referenced in the questions on the survey and in which the statistics are tabulated. For example, the 2019 ABS collection year produces statistics for the 2018 reference year. The "Year" column in the table is the reference year...For more information about ABS planned data product releases, see Tentative ABS Schedule...Key Table Information:.This is the only table in the ABS series to provide information on select economic and demographic characteristics of business owners (CBO) for U.S. employer firms that reported the sex, ethnicity, race, and veteran status for up to four persons owning the largest percentage(s) of the business. The data include estimates for owners of U.S. respondent firms with paid employees operating during the reference year with receipts of $1,000 or more, which are classified in the North American Industry Classification System (NAICS), Sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Owners of employer firms with more than one domestic establishment are counted in each geographic area and industry in which the firm operates, but only once in the U.S. and state totals for all sectors. Firms are asked to report their employees as of the March 12 pay period...Data Items and Other Identifying Records:.Data include estimates on:.Number of owners of respondent employer firms. Percent of number of owners of respondent employer firms (%)...These data are aggregated at the owner level for up to four persons owning the largest percentages of the business by the following demographic classifications:.All owners of respondent firms. Sex. Female. Male. . . Ethnicity. Hispanic. Non-Hispanic. . . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Nonminority (Firms classified as non-Hispanic and White). . . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Nonveteran. . . ...Data Notes:.. Data are tabulated at the owner level.. Respondents are informed that Hispanic origins are not races and are instructed to answer both the Hispanic origin and race questions.. An owner can be tabulated in more than one racial group. This can result because:. The sole owner was reported to be of more than one race.. The majority owner was reported to be of more than one race.. A majority combination of owners was reported to be of more than one race.. . An owner cannot be tabulated with two mutually exclusive demographic classifications (e.g. both as a veteran and a nonveteran.). CBO data are not designed to produce estimates for all U.S. business owners as information was only collected for up to four owners per firm. Researchers analyzing data to create their own estimates are responsible for the validity of those estimates and should cite the Census Bureau as the source of the original data only....Owner Characteristics:.The ABS asked for information for up to four persons owning the largest percentage(s) of the business. Respondent firms include all firms that responded to the characteristics tabulated in this dataset and that reported sex, ethnicity, race, or veteran status for at least one business owner so that the classification of owners of respondent firms by sex, ethnicity, race, and veteran status could be determined. Furthermore, the ABS was designed to include select questions about owner characteristics from multiple reference periods and to incorporate new content each survey year based on topics of relevance. Percentages are for owners of respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a sex, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset...To see the specific survey questions for which estimates are provided in this table, visit the following:... Owner Characteristics collected on the 2019 Annual Business Survey...Industry and Geography Cover...

  4. 2016 Economic Surveys: SE1600CSCBO09 | Statistics for Owners of Respondent...

    • data.census.gov
    Updated Aug 16, 2018
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    ECN (2018). 2016 Economic Surveys: SE1600CSCBO09 | Statistics for Owners of Respondent Employer Firms by Whether the Owner Was Born a U.S. Citizen by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016 (ECNSVY Annual Survey of Entrepreneurs Annual Survey of Entrepreneurs Characteristics of Business Owners) [Dataset]. https://data.census.gov/table/ASECBO2016.SE1600CSCBO09?q=West+Virginia+Populations+and+People&t=Business+and+Economy
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    Dataset updated
    Aug 16, 2018
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2016
    Area covered
    United States
    Description

    Release Date: 2018-08-10.[NOTE: Includes firms with payroll at any time during 2016. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2016 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status for at least one owner and were not publicly held or not classifiable by gender, ethnicity, race, and veteran status. The 2016 Annual Survey of Entrepreneurs asked for information for up to four persons owning the largest percentage(s) of the business. Percentages are for owners of respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for Owners of Respondent Employer Firms by Whether the Owner Was Born a U.S. Citizen by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016. ..Release Schedule. . This file was released in August 2018.. ..Key Table Information. . These data are related to all other 2016 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2016 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2016 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. For Characteristics of Business Owners (CBO) data, all estimates are of owners of firms responding to the ASE. That is, estimates are based only on firms providing gender, ethnicity, race, or veteran status; or firms not classifiable by gender, ethnicity, race, and veteran status that returned an ASE online questionnaire with at least one question answered. The ASE online questionnaire provided space for up to four owners to report their characteristics.. CBO data are not representative of all owners of all firms operating in the United States. The data do not represent all business owners in the United States.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for Owners of Respondent Employer Firms by Whether the Owner Was Born a U.S. Citizen by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016 contains data on:. . Number of owners of respondent firms with paid employees. Percent of number of owners of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of owners of respondent firms. . All owners of respondent firms. Female. Male. Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Nonminority. Veteran. Nonveteran. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years in business. Firms with 11 to 15 years in business. Firms with 16 or more years in business. . . Whether the owner was born a U.S. citizen. . Born a citizen of the Un...

  5. Change in revenue of U.S. small business owners 2010-2017

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). Change in revenue of U.S. small business owners 2010-2017 [Dataset]. https://www.statista.com/statistics/235130/small-business-owners-on-revenue/
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    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    This statistic shows small business owners' responses to a survey question asked from 2010 to 2017, about increases in business revenue. In 2017, 38 percent of small business owners surveyed said revenue had increased in the last year.

  6. 2012 Economic Surveys: SB1200CSCBO08 | Statistics for Owners of Respondent...

    • data.census.gov
    Updated Sep 1, 2016
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    ECN (2016). 2012 Economic Surveys: SB1200CSCBO08 | Statistics for Owners of Respondent Firms by Owner's Age by Gender, Ethnicity, Race, and Veteran Status for the U.S.: 2012 (ECNSVY Survey of Business Owners Survey of Business Owners Characteristics of Business Owners) [Dataset]. https://data.census.gov/all/tables?q=RES%20CONSTRUCTION
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    Dataset updated
    Sep 1, 2016
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2012
    Area covered
    United States
    Description

    Release Date: 2016-02-23.[NOTE: Includes firms with paid employees and firms with no paid employees. Data are based on the 2012 Economic Census, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2012 Survey of Business Owners. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status for at least one owner and were not publicly held or not classifiable by gender, ethnicity, race, and veteran status. The 2012 Survey of Business Owners asked for information for up to four persons owning the largest percentage(s) of the business. Percentages are for owners of respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.].Data User Notice posted on September 1, 2016: Census Bureau staff identified a processing error that affects selected data from the 2012 Survey of Business Owners and Self-Employed Persons (SBO) Statistics, Characteristics of Business Owners tables. As a result, we removed the 2012 "All owners of respondent firms" line from the table. This processing error did not affect other categories in this table. Removed values can be derived by adding the Total reporting and Item not reported rows...Table Name. . Statistics for Owners of Respondent Firms by Owner's Age by Gender, Ethnicity, Race, and Veteran Status for the U.S.: 2012. ..Release Schedule. . The data in this file was released in February 2016.. ..Key Table Information. . This data is related to all other 2012 SBO files.. Refer to the Methodology section of the Survey of Business Owners website for additional information.. ..Universe. . The universe for the 2012 Survey of Business Owners (SBO) includes all U.S. firms operating during 2012 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. For Characteristics of Business Owners (CBO) data, all estimates are of owners of firms responding to the SBO. That is, estimates are based only on firms providing gender, ethnicity, race, or veteran status; or firms not classifiable by gender, ethnicity, race, and veteran status that returned an SBO questionnaire with at least one question answered. The SBO questionnaire provided space for up to four owners to report their characteristics.. CBO data are not representative of all owners of all firms operating in the United States. The data do not represent all business owners in the United States.. ..Geographic Coverage. . The data are shown at the U.S. level only.. ..Industry Coverage. . The data are shown for the total of all sectors (00) and at the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for Owners of Respondent Firms by Owner's Age by Gender, Ethnicity, Race, and Veteran Status for the U.S.: 2012 contains data on:. . Number of owners of respondent firms, respondent firms with paid employees, and respondent firms with no paid employees. Percent of owners of respondent firms, respondent firms with paid employees, and respondent firms with no paid employees. . The data are published by the owner's age as of December 31, 2012, and by gender, ethnicity, race, and veteran status.. ..Sort Order. . Data are presented in ascending levels by:. . Geography (GEO_ID). NAICS code (NAICS2012). Ethnicity, race, and veteran status (CBOGROUP). Gender status (CBOSEX). Owner's age as of December 31, 2012 (OWNRAGE). . The data are sorted on underlying control field values, so control fields may not appear in alphabetical order.. ..FTP Download. . Download the entire SB1200CSCBO08 table at: https://www2.census.gov/programs-surveys/sbo/data/2012/SB1200CSCBO08.zip. ..Contact Information. . To contact the Survey of Business Owners staff:. . Visit the website at www.census.gov/programs-surveys/s...

  7. Opinion on how well business prioritized people during coronavirus U.S. 2020...

    • statista.com
    Updated May 4, 2020
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    Statista (2020). Opinion on how well business prioritized people during coronavirus U.S. 2020 [Dataset]. https://www.statista.com/statistics/1170468/covid-19-opinion-how-well-business-prioritized-people-us/
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    Dataset updated
    May 4, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 15, 2020 - Apr 23, 2020
    Area covered
    United States
    Description

    In an April 2020 online survey, ** percent of participants said that they thought businesses in the United States were putting people before profits during the coronavirus pandemic. Additionally, ** percent said that businesses were protecting their employee's financial wellbeing.

  8. Small Business Contact Data | North American Entrepreneurs | Verified...

    • datarade.ai
    Updated Feb 12, 2018
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    Success.ai (2018). Small Business Contact Data | North American Entrepreneurs | Verified Contact Data & Business Details | Best Price Guaranteed [Dataset]. https://datarade.ai/data-products/small-business-contact-data-north-american-entrepreneurs-success-ai
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    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Feb 12, 2018
    Dataset provided by
    Area covered
    Bermuda, Belize, Nicaragua, Mexico, Honduras, Canada, Guatemala, Saint Pierre and Miquelon, El Salvador, Greenland
    Description

    Success.ai delivers comprehensive access to Small Business Contact Data, tailored to connect you with North American entrepreneurs and small business leaders. Our extensive database includes verified profiles of over 170 million professionals, ensuring direct access to decision-makers in various industries. With AI-validated accuracy, continuously updated datasets, and a focus on compliance, Success.ai empowers businesses to enhance their marketing, sales, and recruitment efforts while staying ahead in a competitive market.

    Key Features of Success.ai's Small Business Contact Data:

    Extensive Coverage: Access profiles for small business owners and entrepreneurs across the United States, Canada, and Mexico. Our database spans multiple industries, from retail to technology, providing diverse business insights.

    Verified Contact Details: Each profile includes work emails, phone numbers, and firmographic data, enabling precise and effective outreach.

    Industry-Specific Data: Target key sectors such as e-commerce, professional services, healthcare, manufacturing, and more, with tailored datasets designed to meet your specific business needs.

    Real-Time Updates: Continuously updated to maintain a 99% accuracy rate, our data ensures that your campaigns are always backed by the most current information.

    Ethical and Compliant: Fully compliant with GDPR and other global data protection regulations, ensuring ethical use of all contact data.

    Why Choose Success.ai for Small Business Contact Data?

    Best Price Guarantee: Enjoy the most competitive pricing in the market, delivering exceptional value for comprehensive and verified contact data.

    AI-Validated Accuracy: Our advanced AI systems meticulously validate every data point to deliver unmatched reliability and precision.

    Customizable Data Solutions: From hyper-targeted regional datasets to comprehensive industry-wide insights, we tailor our offerings to meet your exact requirements.

    Scalable Access: Whether you're a startup or an enterprise, our solutions are designed to scale with your business needs.

    Comprehensive Use Cases for Small Business Contact Data:

    1. Targeted Marketing Campaigns:

    Refine your marketing strategy by leveraging verified contact details for small business owners. Execute highly personalized email, phone, and multi-channel campaigns with precision.

    1. Sales Prospecting:

    Identify and connect with decision-makers in key industries. Use detailed profiles to enhance your sales outreach, close deals faster, and build long-term client relationships.

    1. Recruitment and Talent Acquisition:

    Discover small business leaders and key players in specific industries to strengthen your recruitment pipeline. Access up-to-date profiles for sourcing top talent.

    1. Market Research:

    Gain insights into small business trends, operational challenges, and industry benchmarks. Leverage this data for competitive analysis and market positioning.

    1. Local Business Engagement:

    Foster partnerships with small businesses by identifying community leaders and entrepreneurial influencers in your target regions.

    APIs to Enhance Your Campaigns:

    Enrichment API: Integrate real-time updates into your CRM and marketing systems to maintain accurate and actionable contact data. Perfect for businesses looking to improve lead quality.

    Lead Generation API: Maximize your lead generation efforts with access to verified contact details, including emails and phone numbers. Tailored for precise targeting of small business decision-makers.

    Tailored Solutions for Diverse Needs:

    Marketing Agencies: Create targeted campaigns with verified data for small business owners across diverse sectors.

    Sales Teams: Drive revenue growth with detailed profiles and direct access to decision-makers.

    Recruiters: Build a talent pipeline with current and verified data on small business leaders and professionals.

    Consultants: Provide data-driven recommendations to clients by leveraging detailed small business insights.

    What Sets Success.ai Apart?

    170M+ Profiles: Access a vast and detailed database of small business owners and entrepreneurs.

    Global Standards Compliance: Rest assured knowing all data is ethically sourced and compliant with global privacy regulations.

    Flexible Integration: Seamlessly integrate data into your existing workflows with customizable delivery options.

    Dedicated Support: Our team of experts is always available to ensure you maximize the value of our solutions.

    Empower Your Outreach with Success.ai:

    Success.ai’s Small Business Contact Data is your gateway to building meaningful connections with North American entrepreneurs. Whether you're driving targeted marketing campaigns, enhancing sales prospecting, or conducting in-depth market research, our verified datasets provide the tools you need to succeed.

    Get started with Success.ai today and unlock the potential of verified Small Business ...

  9. Share of French people who want to create their own company 2023

    • statista.com
    Updated Jun 17, 2025
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    Statista (2025). Share of French people who want to create their own company 2023 [Dataset]. https://www.statista.com/statistics/1011154/desire-to-create-its-company-by-gender-france/
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    Dataset updated
    Jun 17, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 15, 2023 - Feb 21, 2023
    Area covered
    France
    Description

    This statistic shows the percentage of French people who would want to start their own business someday or take over one in a survey from 2023. It reveals that most of the respondents stated certainly not wanting to create or manage their own company. However, for almost 50 percent of young people, creating a business was actually an appealing idea.

  10. Private enterprises by ownership gender, age group of primary owner and...

    • www150.statcan.gc.ca
    • open.canada.ca
    • +1more
    Updated Mar 22, 2022
    + more versions
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    Government of Canada, Statistics Canada (2022). Private enterprises by ownership gender, age group of primary owner and enterprise size, inactive [Dataset]. http://doi.org/10.25318/3310019201-eng
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    Dataset updated
    Mar 22, 2022
    Dataset provided by
    Government of Canadahttp://www.gg.ca/
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    The total number and percentage of private enterprises owned by men or women, by age group of primary owner and enterprise size.

  11. Future of Business Survey 2020 - Albania, Algeria, American Samoa...and 176...

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Sep 3, 2025
    + more versions
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    Facebook (2025). Future of Business Survey 2020 - Albania, Algeria, American Samoa...and 176 more [Dataset]. https://microdata.worldbank.org/index.php/catalog/4212
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    Dataset updated
    Sep 3, 2025
    Dataset provided by
    World Bank Grouphttp://www.worldbank.org/
    Organisation for Economic Co-operation and Developmenthttp://oecd.org/
    Facebook
    Time period covered
    2020
    Area covered
    Algeria, American Samoa
    Description

    Abstract

    The Future of Business Survey is a new source of information on small and medium-sized enterprises (SMEs). Launched in February 2016, the monthly survey - a partnership between Facebook, OECD, and The World Bank - provides a timely pulse on the economic environment in which businesses operate and who those businesses are to help inform decision-making at all levels and to deliver insights that can help businesses grow. The Future of Business Survey provides a perspective from newer and long-standing digitalized businesses and provides a unique window into a new mobilized economy.

    Policymakers, researchers and businesses share a common interest in the environment in which SMEs operate, as well their outlook on the future, not least because young and innovative SMEs in particular are often an important source of considerable economic and employment growth. Better insights and timely information about SMEs improve our understanding of economic trends, and can provide new insights that can further stimulate and help these businesses grow.

    To help provide these insights, Facebook, OECD and The World Bank have collaborated to develop a monthly survey that attempts to improve our understanding of SMEs in a timely and forward-looking manner. The three organizations share a desire to create new ways to hear from businesses and help them succeed in the emerging digitally-connected economy. The shared goal is to help policymakers, researchers, and businesses better understand business sentiment, and to leverage a digital platform to provide a unique source of information to complement existing indicators.

    With more businesses leveraging online tools each day, the survey provides a lens into a new mobilized, digital economy and, in particular, insights on the actors: a relatively unmeasured community worthy of deeper consideration and considerable policy interest.

    Geographic coverage

    When the survey was initially launched in February 2016, it included 22 countries. When the survey was initially launched in February 2016, it included 22 countries. The Future of Business Survey is now conducted in over 90 countries in every region of the world.

    Countries included in at least one wave: Albania Algeria American Samoa Andorra Angola Anguilla Antigua and Barbuda Argentina Aruba Australia Austria Azerbaijan Bahamas (the) Bangladesh Barbados Belarus Belgium Belize Benin Bolivia (Plurinational State of) Bonaire, Sint Eustatius and Saba Bosnia and Herzegovina Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cabo Verde Cambodia Cameroon Canada Cayman Islands (the) Central African Republic (the) Chad Chile Colombia Congo (the) Curaçao Cyprus Czechia Côte d'Ivoire Denmark Djibouti Dominica Dominican Republic (the) Ecuador Egypt El Salvador Equatorial Guinea Estonia Eswatini Ethiopia Faroe Islands (the) Fiji Finland France French Polynesia Gabon Gambia (the) Germany Ghana Gibraltar Greece Grenada Guadeloupe Guam Guatemala Guernsey Guinea Guinea-Bissau Guyana Haiti Honduras Hong Kong Hungary Iceland India Indonesia Iraq Ireland Isle of Man Israel Italy Jamaica Japan Jersey Jordan Kenya Korea (the Republic of) Kuwait Lao People's Democratic Republic (the) Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Malawi Malaysia Mali Malta Martinique Mauritania Mauritius Mayotte Mexico Monaco Montenegro Morocco Mozambique Myanmar Namibia Nepal Netherlands (the) New Caledonia New Zealand Nicaragua Niger (the) Nigeria North Macedonia Northern Mariana Islands (the) Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines (the) Poland Portugal Qatar Romania Russian Federation (the) Rwanda Réunion Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Sint Maarten (Dutch part) Slovakia Slovenia Solomon Islands South Africa Spain Sweden Switzerland Taiwan Tanzania, the United Republic of Thailand Timor-Leste Togo Tonga Trinidad and Tobago Tunisia Turkey Turks and Caicos Islands (the) Uganda United Arab Emirates (the) United Kingdom of Great Britain and Northern Ireland (the) United States of America (the) Uruguay Vanuatu Viet Nam Virgin Islands (British) Virgin Islands (U.S.) Zambia.

    Analysis unit

    The study describes small and medium-sized enterprises.

    Universe

    The target population consists of SMEs that have an active Facebook business Page and include both newer and longer-standing businesses, spanning across a variety of sectors. With more businesses leveraging online tools each day, the survey provides a lens into a new mobilized, digital economy and, in particular, insights on the actors: a relatively unmeasured community worthy of deeper consideration and considerable policy interest.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Twice a year in over 97 countries, the Facebook Survey Team sends the Future of Business to admins and owners of Facebook-designated small business pages. When we share data from this survey, we anonymize responses to all survey questions and only share country-level data publicly. To achieve better representation of the broader small business population, we also weight our results based on known characteristics of the Facebook Page admin population.

    A random sample of firms, representing the target population in each country, is selected to respond to the Future of Business Survey each month.

    Mode of data collection

    Internet [int]

    Research instrument

    The survey includes questions about perceptions of current and future economic activity, challenges, business characteristics and strategy. Custom modules include questions related to regulation, access to finance, digital payments, and digital skills. The full questionnaire is available for download.

    Response rate

    Response rates to online surveys vary widely depending on a number of factors including survey length, region, strength of the relationship with invitees, incentive mechanisms, invite copy, interest of respondents in the topic and survey design.

    Note: Response rates are calculated as the number of respondents who completed the survey divided by the total number of SMEs invited.

    Sampling error estimates

    Any survey data is prone to several forms of error and biases that need to be considered to understand how closely the results reflect the intended population. In particular, the following components of the total survey error are noteworthy:

    Sampling error is a natural characteristic of every survey based on samples and reflects the uncertainty in any survey result that is attributable to the fact that not the whole population is surveyed.

    Other factors beyond sampling error that contribute to such potential differences are frame or coverage error (sampling frame of page owners does not include all relevant businesses but also may include individuals that don't represent businesses), and nonresponse error.

    Note that the sample is meant to reflect the population of businesses on Facebook, not the population of small businesses in general. This group of digitized SMEs is itself a community worthy of deeper consideration and of considerable policy interest. However, care should be taken when extrapolating to the population of SMEs in general. Moreover, future work should evaluate the external validity of the sample. Particularly, respondents should be compared to the broader population of SMEs on Facebook, and the economy as a whole.

  12. w

    Survey of Businesses Receiving The People's Business Credit 2021 - Indonesia...

    • microdata.worldbank.org
    • datacatalog.ihsn.org
    • +1more
    Updated Aug 13, 2024
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    Coordinating Ministry for Economic Affairs (2024). Survey of Businesses Receiving The People's Business Credit 2021 - Indonesia [Dataset]. https://microdata.worldbank.org/index.php/catalog/6282
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    Dataset updated
    Aug 13, 2024
    Dataset authored and provided by
    Coordinating Ministry for Economic Affairs
    Time period covered
    2021
    Area covered
    Indonesia
    Description

    Abstract

    In 2007, the Government of Indonesia launched the “People’s Business Loan” (Kredit Usaha Rakyat, KUR) program as a flagship public program to enhance MSMEs’ access to finance. Since its inception, KUR has grown into one of the world’s largest public support programs for MSMEs. This survey includes a nationally representative sample of 1,402 KUR borrowers who received micro or small KUR loans between December 2015 and March 2020. The survey covers basic business information, business practices, workers, revenue, financial history prior to receiving KUR for the first time, and financial history after receiving KUR for the first time. In addition, firms were asked one of two of the following modules: experiences with the KUR program or impact of COVID-19 on the business. The data was collected by phone in January and February 2021, and weighted stratified sampling was used to ensure a representative sample and enable subgroup analysis.

    Geographic coverage

    Nationally representative survey of KUR borrowers

    Analysis unit

    Business

    Universe

    Businesses who received KUR loans between December 2015 and March 2020.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    An administrative database (SIKP), which contains basic characteristics of all KUR borrowers since 2016, served as the sampling frame for the quantitative data collection. Weighted stratified random sampling was used to select the sample. Strata were based on four characteristics that may influence beneficiaries’ experiences with KUR and how KUR may change their business: gender of KUR recipient, size of KUR loan, financial institution that issued the KUR loan, and geographic region. Strata including less than 1% of KUR beneficiaries were oversampled in order to ensure that each subgroup of interest would have sufficient representation in the sample in order to draw precise estimates at the subgroup level.

    Stratified sampling methodology was chosen because the team wanted to ensure that subgroup analysis was feasible across certain dimensions. Some of the subgroups of interest represent only a small portion of KUR borrowers, so a random sampling approach without using strata may not have provided a sufficient number of observations to draw any conclusions about some of these subgroups. Gender was included as a stratification variable to ensure that a gender-sensitive analysis was feasible. Female entrepreneurs in Indonesia face greater financing constraints than male entrepreneurs (World Bank 2023), so KUR may have particularly strong impacts for female entrepreneurs. Nevertheless, the market-based implementation of KUR may also limit the ability of KUR to reach female entrepreneurs, if it does not alleviate gendered constraints to accessing financing. Micro KUR loans and small KUR loans have different requirements and offer different sizes of subsidies to the KUR distributors. As such, it is critical to be able to analyze them separately. Because less than 10 percent of KUR loans are small KUR loans, stratification on this variable ensures that there is enough statistical power to draw conclusions about small KUR loans. One financial institution, BRI, issues the majority of KUR loans. Because KUR is implemented by different distributors and some aspects of implementation are left to the distributor’s discretion, it is important to understand whether the implementation of KUR looks different when issued by the dominant bank or when issued by other distributors. Finally, financing conditions and alternatives vary across geography. Because the environment may shift how important KUR is to MSMEs, it is important to be able to understand how trends vary across different regions. Some regions have less than 10 percent of KUR borrowers in them, so a simple random selection may not have produced enough observations in some regions to allow for analysis disaggregated by region.

    Generally, strata including firms with KUR loans of more than 25 million and those outside of Jawa were over-sampled, while firms receiving loans of less than 25 million in Jawa were under-sampled to ensure the total sample size rested within budget and logistical constraints. Finally, an even number of firms were selected for the sample from each strata so that they can be split into halves, where one half would answer the modules in questionnaire A and the other half would answer modules in questionnaire B. This allows the design weights to remain constant for all variables in the survey and facilitates data analysis. The modules to be asked were randomly assigned and balanced across sampling strata to ensure all modules included nationally representative information. Due to the weighted sampling design, design weights are used in all descriptive analysis in this report, and once incorporating the design weights the analysis is representative of all KUR recipients since 2016.

    The survey firm received a randomized order list of firms within each strata and were instructed to call respondents until reaching the quota per strata.

    Sampling deviation

    In practice, there were two extra interviews conducted, leading to a total number of interviews of 1,402 instead of the targeted 1,400 interviews. The design weights used in the analysis were adjusted to the actual number of interviews conducted in each strata.

    Mode of data collection

    Other [oth]

    Response rate

    Overall, 10,789 phone-calls were attempted. Of these calls, about 30 percent of the calls were not connected and classified as ‘voice mail’, 15 percent were notified that the number is inactive, and 13 percent were notified that the number is not registered. 28 percent of the overall phone-call attempts were connected, and 13 percent were successfully interviewed.

  13. g

    US Census, Summary Statistics for Changes in the Number of Women-Owned...

    • geocommons.com
    Updated Jun 2, 2008
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    2002 SURVEY OF BUSINESS OWNERS (SBO) (2008). US Census, Summary Statistics for Changes in the Number of Women-Owned Businesses and their Receipts, USA, 1997-2002 [Dataset]. http://geocommons.com/search.html
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    Dataset updated
    Jun 2, 2008
    Dataset provided by
    matia
    2002 SURVEY OF BUSINESS OWNERS (SBO)
    Description

    This SBO dataset explores women-owned businesses and their receipts in the USA from 1997-2002. The Survey of Business owners (SBO) is a consolidation of two prior surveys, the Surveys of Minority- and Women-Owned Business Enterprises (SMOBE/SWOBE), and includes questions from a survey discontinued in 1992 on Characteristics of Business Owners (CBO).

  14. Future of Business Survey 2016-2018 - Argentina, Australia, Bangladesh...and...

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Oct 26, 2023
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    Facebook (2023). Future of Business Survey 2016-2018 - Argentina, Australia, Bangladesh...and 38 more [Dataset]. https://microdata.worldbank.org/index.php/catalog/4211
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    Dataset updated
    Oct 26, 2023
    Dataset provided by
    World Bank Grouphttp://www.worldbank.org/
    Organisation for Economic Co-operation and Developmenthttp://oecd.org/
    Facebook
    Time period covered
    2016 - 2018
    Area covered
    Australia, Bangladesh, Argentina
    Description

    Abstract

    The Future of Business Survey is a new source of information on small and medium-sized enterprises (SMEs). Launched in February 2016, the monthly survey - a partnership between Facebook, OECD, and The World Bank - provides a timely pulse on the economic environment in which businesses operate and who those businesses are to help inform decision-making at all levels and to deliver insights that can help businesses grow. The Future of Business Survey provides a perspective from newer and long-standing digitalized businesses and provides a unique window into a new mobilized economy.

    Policymakers, researchers and businesses share a common interest in the environment in which SMEs operate, as well their outlook on the future, not least because young and innovative SMEs in particular are often an important source of considerable economic and employment growth. Better insights and timely information about SMEs improve our understanding of economic trends, and can provide new insights that can further stimulate and help these businesses grow.

    To help provide these insights, Facebook, OECD and The World Bank have collaborated to develop a monthly survey that attempts to improve our understanding of SMEs in a timely and forward-looking manner. The three organizations share a desire to create new ways to hear from businesses and help them succeed in the emerging digitally-connected economy. The shared goal is to help policymakers, researchers, and businesses better understand business sentiment, and to leverage a digital platform to provide a unique source of information to complement existing indicators.

    With more businesses leveraging online tools each day, the survey provides a lens into a new mobilized, digital economy and, in particular, insights on the actors: a relatively unmeasured community worthy of deeper consideration and considerable policy interest.

    Geographic coverage

    When the survey was initially launched in February 2016, it included 22 countries. When the survey was initially launched in February 2016, it included 22 countries. The Future of Business Survey is now conducted in over 90 countries in every region of the world.

    Analysis unit

    The study describes small and medium-sized enterprises.

    Universe

    The target population consists of SMEs that have an active Facebook business Page and include both newer and longer-standing businesses, spanning across a variety of sectors. With more businesses leveraging online tools each day, the survey provides a lens into a new mobilized, digital economy and, in particular, insights on the actors: a relatively unmeasured community worthy of deeper consideration and considerable policy interest.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Twice a year in over 97 countries, the Facebook Survey Team sends the Future of Business to admins and owners of Facebook-designated small business pages. When we share data from this survey, we anonymize responses to all survey questions and only share country-level data publicly. To achieve better representation of the broader small business population, we also weight our results based on known characteristics of the Facebook Page admin population.

    A random sample of firms, representing the target population in each country, is selected to respond to the Future of Business Survey each month.

    Mode of data collection

    Internet [int]

    Research instrument

    The survey includes questions about perceptions of current and future economic activity, challenges, business characteristics and strategy. Custom modules include questions related to regulation, access to finance, digital payments, and digital skills. The full questionnaire is available for download.

    The questionnaire was pretested by the target audience, as well as experts from the area of research interest. Additionally, steps were taken to translate the survey in order to reduce sensitivities to cultural response bias: - Respondents were given the option to respond to the survey in any of fifteen languages native to the countries in which it was conducted. - Translations were done only by native speakers, with two rounds of additional online checks in the context of the survey environment. - Translators were provided with context material for this survey (e.g., the Facebook for Business website) in order to understand the context of the survey. They were also instructed to take the English survey at least two times before starting with the translations. - Translations were discussed in a group in order to ensure a common understanding of questions and items. - The tone (formal vs. informal) of the survey was based on cultural conventions, e.g., Facebook usually uses an informal tone, while in cultures such as the Japanese this is very uncommon and thus a formal tone was used there.

    Response rate

    Response rates to online surveys vary widely depending on a number of factors including survey length, region, strength of the relationship with invitees, incentive mechanisms, invite copy, interest of respondents in the topic and survey design.

    Note: Response rates are calculated as the number of respondents who completed the survey divided by the total number of SMEs invited.

    Sampling error estimates

    Any survey data is prone to several forms of error and biases that need to be considered to understand how closely the results reflect the intended population. In particular, the following components of the total survey error are noteworthy:

    Sampling error is a natural characteristic of every survey based on samples and reflects the uncertainty in any survey result that is attributable to the fact that not the whole population is surveyed.

    Other factors beyond sampling error that contribute to such potential differences are frame or coverage error (sampling frame of page owners does not include all relevant businesses but also may include individuals that don't represent businesses), and nonresponse error.

    Note that the sample is meant to reflect the population of businesses on Facebook, not the population of small businesses in general. This group of digitized SMEs is itself a community worthy of deeper consideration and of considerable policy interest. However, care should be taken when extrapolating to the population of SMEs in general. Moreover, future work should evaluate the external validity of the sample. Particularly, respondents should be compared to the broader population of SMEs on Facebook, and the economy as a whole.

  15. Share of French people who want to create their own company 2020, by age

    • statista.com
    Updated Jul 4, 2024
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    Statista (2024). Share of French people who want to create their own company 2020, by age [Dataset]. https://www.statista.com/statistics/1011160/desire-to-create-its-company-by-age-france/
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    Dataset updated
    Jul 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2, 2020 - Jan 8, 2020
    Area covered
    France
    Description

    This statistic shows the percentage of French people who would want to start their own business someday or take over one in a survey from 2020, distributed by age. It displays that a wide majority of respondents aged 50 years old and over, 85 percent, did not want to create or manage their own company. On the other hand, 43 percent of people aged 18 to 24 years old declared that they would probably like to have their own business, and the proportion was more than half for those aged 25-34.

  16. s

    Entrepreneurs In The United States

    • searchlogistics.com
    Updated Apr 1, 2025
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    (2025). Entrepreneurs In The United States [Dataset]. https://www.searchlogistics.com/learn/statistics/entrepreneurial-statistics/
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    Dataset updated
    Apr 1, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    There are more than 31 million entrepreneurs in the US alone.

  17. Early-stage entrepreneurial activity rate in Europe, by country 2024

    • statista.com
    • tokrwards.com
    • +1more
    Updated Sep 12, 2025
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    Statista (2025). Early-stage entrepreneurial activity rate in Europe, by country 2024 [Dataset]. https://www.statista.com/statistics/315502/percentage-of-population-involved-in-business-start-ups-in-europe/
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    Dataset updated
    Sep 12, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Europe
    Description

    In Europe, the share of the adult population involved in the early stage of a start-up varied between 14 percent in the United Kingdom and *********** in Poland. The total early-stage entrepreneurial activity (TEA) rate is defined as the prevalence rate of individuals in the working age population who are actively involved in business startups, either in the phase in advance of the birth of the firm (nascent entrepreneurs), or the phase spanning 42 months after the birth of the firm (owner managers of new firms).

  18. Appendix 1. Statistical Descriptive: Table 1.6 The Aggregate (Population)...

    • figshare.com
    png
    Updated May 15, 2025
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    Muhammad Andi Abdillah Triono (2025). Appendix 1. Statistical Descriptive: Table 1.6 The Aggregate (Population) Data of The Ownership of Business Licences in Medan City [Dataset]. http://doi.org/10.6084/m9.figshare.28905032.v2
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    pngAvailable download formats
    Dataset updated
    May 15, 2025
    Dataset provided by
    figshare
    Authors
    Muhammad Andi Abdillah Triono
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Medan, Medan City
    Description

    Disclaimer:The raw data originates from the Medan City administration's aggregate MSME data. The researcher obtained research permit number 000.9/1826 in 2023 and received authorization from the Medan City Government to analyze and publish this data.Interpretation:This table presents data on business licence ownership across 21 districts in the city of Medan. It categorises individuals as those who own business licenses ("yes") and those who do not ("no") with a total count for each district.Key Insights:Overall Business License Ownership:7,034 individuals (7.80%) have registered business licences.83,157 individuals (92.20%) do not own business licences.Districts with the Highest Business License Ownership:Medan Tuntungan: 3,078 licences issued (43.77% of total licence owners).Medan Tembung: 2,170 licenses (30.86%).Medan Area: 820 licences (11.66%).Districts with the Lowest Business License Ownership:Medan Labuhan: two licenses (0.03%).Medan Maimun: 2 licences (0.03%).Medan Belawan: 3 licences (0.04%).General Trend:The distribution suggests that certain districts, such as Medan Tuntungan and Medan Tembung, have a significantly higher number of registered businesses, possibly due to economic activity or local policies that encourage formalisation.Meanwhile, districts like Medan Labuhan and Medan Belawan have virtually very few registered businesses, which may indicate challenges in business regulation or a predominance of informal enterprises.Potential Research Implications:Entrepreneurship Formalisation: The low percentage of registered businesses suggests potential barriers to formal business registration.District-Level Economic Activity: The variations in licence ownership may reflect differences in commercial density across districts.Policy considerations: Understanding why certain districts have greater license ownership could help shape local regulations that incentivise formal business registration.

  19. 2021 Economic Surveys: AB2100CSCBO | Annual Business Survey: Owner...

    • data.census.gov
    Updated Oct 26, 2023
    + more versions
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    ECN (2023). 2021 Economic Surveys: AB2100CSCBO | Annual Business Survey: Owner Characteristics of Respondent Employer Firms by Industry, Sex, Ethnicity, Race, and Veteran Status for the U.S., States, and Metro Areas: 2021 (ECNSVY Annual Business Survey Characteristics of Business Owners) [Dataset]. https://data.census.gov/table/ABSCBO2021.AB2100CSCBO?&n=00&nkd=OWNER_ETH%7E001,OWNER_RACE%7E90,OWNER_SEX%7E001,OWNER_VET%7E001,QDESC%7EO07
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    Dataset updated
    Oct 26, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2021
    Area covered
    United States
    Description

    Release Date: 2023-10-26.The Census Bureau has reviewed this data product for unauthorized disclosure of confidential information and has approved the disclosure avoidance practices applied (Approval ID: CBDRB-FY23-0479)...Release Schedule:.Data in this file come from estimates of business ownership by sex, ethnicity, race, and veteran status from the 2022 Annual Business Survey (ABS) collection. Data are also obtained from administrative records, the 2017 Economic Census, and other economic surveys...Note: The collection year is the year in which the data are collected. A reference year is the year that is referenced in the questions on the survey and in which the statistics are tabulated. For example, the 2022 ABS collection year produces statistics for the 2021 reference year. The "Year" column in the table is the reference year...For more information about ABS planned data product releases, see Tentative ABS Schedule...Key Table Information:.This is the only table in the ABS series to provide information on select economic and demographic characteristics of business owners (CBO) for U.S. employer firms that reported the sex, ethnicity, race, and veteran status for up to four persons owning the largest percentage(s) of the business. The data include estimates for owners of U.S. respondent firms with paid employees operating during the reference year with receipts of $1,000 or more, which are classified in the North American Industry Classification System (NAICS), Sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Owners of employer firms with more than one domestic establishment are counted in each geographic area and industry in which the firm operates, but only once in the U.S. and state totals for all sectors. Firms are asked to report their employees as of the March 12 pay period...Data Items and Other Identifying Records:.Data include estimates on:.Number of owners of respondent employer firms. Percent of number of owners of respondent employer firms (%)...These data are aggregated at the owner level for up to four persons owning the largest percentages of the business by the following demographic classifications:.All owners of respondent firms. Sex. Female. Male. . . Ethnicity. Hispanic. Non-Hispanic. . . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Nonminority (Firms classified as non-Hispanic and White). . . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Nonveteran. . . ...Data Notes:.. Data are tabulated at the owner level.. Respondents are informed that Hispanic origins are not races and are instructed to answer both the Hispanic origin and race questions.. An owner can be tabulated in more than one racial group. This can result because:. The sole owner was reported to be of more than one race.. The majority owner was reported to be of more than one race.. A majority combination of owners was reported to be of more than one race.. . An owner cannot be tabulated with two mutually exclusive demographic classifications (e.g. both as a veteran and a nonveteran.). CBO data are not designed to produce estimates for all U.S. business owners as information was only collected for up to four owners per firm. Researchers analyzing data to create their own estimates are responsible for the validity of those estimates and should cite the Census Bureau as the source of the original data only.. Percent values may exceed 100 due to noise....Owner Characteristics:.The ABS asked for information for up to four persons owning the largest percentage(s) of the business. Respondent firms include all firms that responded to the characteristics tabulated in this dataset and that reported sex, ethnicity, race, or veteran status for at least one business owner so that the classification of owners of respondent firms by sex, ethnicity, race, and veteran status could be determined. Furthermore, the ABS was designed to include select questions about owner characteristics from multiple reference periods and to incorporate new content each survey year based on topics of relevance. Percentages are for owners of respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a sex, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset...Owner characteristic topics for the 2022 ABS included in this table are the following: ..Year Acquired Ownership of Business (YRACQBUS).Primary Source of Income...

  20. i

    GET Ahead Business Training Program Impact Evaluation 2013 - 2017 - Kenya

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Mar 29, 2019
    + more versions
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    David McKenzie (2019). GET Ahead Business Training Program Impact Evaluation 2013 - 2017 - Kenya [Dataset]. https://datacatalog.ihsn.org/catalog/4528
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    David McKenzie
    Time period covered
    2013 - 2017
    Area covered
    Kenya
    Description

    Abstract

    We conduct a randomized experiment in 157 rural markets in Kenya to test how business training (the International Labour Organization (ILO)'s Gender and Enterprise Together program) affects the profitability, growth and survival of female-owned businesses, and to evaluate whether any gains in profitability come at the expense of other business owners. We work with a large sample of 3,537 firms, and use a two-stage randomization, first randomizing at the market-level, and then randomizing the offer of training to individuals within treated markets. A year and a half after the training has taken place, half of the sample assigned to training was then offered a subsequent mentoring intervention intended to test whether additional group-based and in-person support strengthens the impacts of training. Four rounds of follow-up surveys with low attrition are used to measure impacts at one and three years after training. This is complimented with data from a market census taken four years after training, that also included male-operated firms.

    Geographic coverage

    Kakamega and Kisii counties in the Western region, and Embu and Kitui counties in the Eastern region.

    Analysis unit

    • Individual female microenterprise
    • Firm

    Universe

    Women operating in markets in four counties in Kenya: Kakamega and Kisii in the Western region, and Embu and Kitui in the Eastern region

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The selection of the study areas was the result of a participatory process that involved the Technical Committee of the ILO Women Entrepreneurship and Economic Empowerment (WEDEE) project as well as other relevant stakeholders. A Stakeholder retreat in October 2012 was used to pre-select 10 counties from the 47 counties in Kenya as possible locations for the study. A more detailed review of these 10 counties and consultations with the stakeholders were then used to select 4 counties in which to provide the ILO Gender and Entrepreneurship Together (GET Ahead) training: Kakamega and Kisii in the Western region, and Embu and Kitui in the Eastern region.

    In each of Kakamega, Kisii, Embu and Kitui counties field staff from Innovations for Poverty Action, Kenya, mapped out all market centers deemed as medium or large outside of the main cities. Field staff then conducted a market census, applying a 31-question listing questionnaire to each female-owned enterprise operating on a non-market day in these markets. This questionnaire took a median time of 15 minutes to complete, and collected data on business type, education, age, profits and sales, membership in women's associations or merry-go-rounds, and contact follow-up information. The listing operation took place one county at a time between June 3, 2013 and November 1, 2013.

    After the census, three markets in Kakamega county were dropped because the number of women in these markets was too few. Researchers then applied an eligibility filter to determine which women to include in the baseline survey. This filter required the women to have reported profits, and not to have reported profits that exceeded sales; to have a phone number that could be used to invite them for training; to be 55 years old or younger; to not be running a business that only dealt with phone cards or m-pesa, or that was a school; that the person responding not be an employee; that the business not have more than 3 employees; that the business have profits in the past week between 0 and 4000 KSH; that sales in the past week be less than or equal to 50,000 KSH; and that the individual had at least one year of schooling. These criteria were chosen to reduce the amount of heterogeneity in the sample (thereby increasing our ability to detect treatment effects), and to increase the odds of being able to contact and find individuals again.

    Applying this eligibility filter reduced the 6,296 individuals to 4,037 individuals (64%). Out of a target of 4,037 individuals, the team was able to interview 3,538 (87.6%) in time to consider them for inviting to training.

    Randomization process

    The individuals who had satisfied the screening criteria and completed the baseline survey were then assigned to treatment and control in a two-stage process:

    First, markets were assigned to treatment (have some individuals in them invited to training) or control (no one in the market would be invited to training) status. Randomization was done within 35 strata defined by geographical region (within county) and the number of women surveyed in the market.

    Then within each market, individuals were assigned to treatment (be invited to training) or control (not be invited to training) within treated markets by forming four strata, based on quartiles of weekly profits from the census (<=450, 451-800, 801-1500, 1501-4000), and then assigning half the individuals within each strata to training. When the number of individuals in the strata was odd, the odd unit was also randomly assigned to training. This resulted in 1,173 of the 2,161 individuals in treated markets being assigned to treatment, and 988 to control groups.

    Additoinal details on sampling are abailable in Section 2 of the Working Paper provided under Related Materials.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    The following survey instruments were used for data collection: - Census of Women Entrepreneurs - Baseline Questionnaire - Long Follow-up Surveys (Rounds 2 and 4) - Short Follow-up Surveys (Rounds 3 and 5) - Market Census Questionnaires (Rounds 2 and 4) - Final Market Questionnaire - Customer Survey Questionnaire

    The Market census questionnaire took a median time of 15 minutes to complete. It collected data on business type, education, age, profits and sales, membership in women's associations or merry-go-rounds, and contact follow-up information. The baseline questionnaire took a median time of 90 minutes to complete. The 30-page questionnaire asked detailed questions about the business owner, her family and business activities.

    Response rate

    Overall we were able to interview 95.0 percent of the sample in at least one of round 2 or 3, and 92.3 percent in at least one of round 4 or 5. In addition, in cases where we were unable to interview someone due to refusal, travel, death, or other reasons, we collected information from other household members or close contacts on whether the individual in our sample was currently operating a business. This enables us to have data on survival status for 99.3 percent of the sample at one year, and 97.2 percent at three years. There is no significant difference in data availability with treatment status at the three year horizon, although those assigned to treatment are 1 to 2 percentage points more likely to have data available at the one year horizon. See Appendix Table 2 of the working paper provided under Related Materials details response rates.

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Statista (2025). Share of people who have started their own business by country 2021 [Dataset]. https://www.statista.com/statistics/948475/share-people-started-their-own-business-country/
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Share of people who have started their own business by country 2021

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2 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jul 9, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Nov 20, 2020 - Dec 4, 2020
Area covered
Worldwide
Description

According to data published by IPSOS in 2021, ** percent of respondents from Peru have started at least one business, compared to ***** percent of respondents from Japan.

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